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    <description>The evolution of enterprise AI. We talk ideas, research and theories as they apply to the real world.</description>
    <copyright>© 2026 Zeroe</copyright>
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    <pubDate>Thu, 20 Aug 2026 03:13:57 -0700</pubDate>
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    <itunes:summary>The evolution of enterprise AI. We talk ideas, research and theories as they apply to the real world.</itunes:summary>
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      <title>The End of the Knowlege Moat</title>
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      <itunes:title>The End of the Knowlege Moat</itunes:title>
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        <![CDATA[<p><strong>Zeroe Perspectives, Episode 1: The Knowledge Moat Is Ending</strong></p><p><br>For decades, deep industry knowledge was a competitive advantage.</p><p>It was valuable, scarce and difficult to replicate because it took years, sometimes decades, to accumulate.</p><p>AI is changing that.</p><p>Frontier models can now access and apply enormous amounts of specialised knowledge in seconds. What once required years of experience is becoming increasingly available to everyone.</p><p>So if your competitors can access the same intelligence you can, where does competitive advantage come from?</p><p><br>In the first episode of <strong>Zeroe Perspectives</strong>, Eric and Christina explore the idea that the traditional knowledge moat is disappearing, and that a new moat is beginning to emerge: <strong>organisational judgment</strong>.</p><p><br>They discuss the difference between industry knowledge and company-specific context, why enterprise AI often struggles despite increasingly capable models, and why simply giving employees access to ChatGPT, Claude or Copilot does not necessarily make the organisation itself smarter.</p><p><br>The conversation explores:</p><ul><li>Why AI is making general industry knowledge less scarce</li><li>The difference between knowledge, context and judgment</li><li>Why enterprise AI needs to understand how a company actually operates</li><li>How institutional knowledge gets lost when experienced employees leave</li><li>The role of tacit knowledge in business decision-making</li><li>Why companies capture decisions but often fail to capture the reasoning behind them</li><li>How employees currently act as the manual context layer between AI and the enterprise</li><li>Why AI adoption should be measured by more than licences and usage</li><li>How organisational memory can become decision infrastructure</li><li>Why the next competitive advantage may be something your competitors cannot simply buy</li></ul><p>The first phase of enterprise AI was about giving people access to intelligence.</p><p>The next phase is about giving that intelligence context.</p><p>And the companies that learn how to capture and encode their history, reasoning, exceptions and judgment may build something far more defensible than access to any single model.</p><p><strong>Zeroe Perspectives</strong> explores the evolution of enterprise AI, and what changes when intelligence becomes abundant.</p>]]>
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        <![CDATA[<p><strong>Zeroe Perspectives, Episode 1: The Knowledge Moat Is Ending</strong></p><p><br>For decades, deep industry knowledge was a competitive advantage.</p><p>It was valuable, scarce and difficult to replicate because it took years, sometimes decades, to accumulate.</p><p>AI is changing that.</p><p>Frontier models can now access and apply enormous amounts of specialised knowledge in seconds. What once required years of experience is becoming increasingly available to everyone.</p><p>So if your competitors can access the same intelligence you can, where does competitive advantage come from?</p><p><br>In the first episode of <strong>Zeroe Perspectives</strong>, Eric and Christina explore the idea that the traditional knowledge moat is disappearing, and that a new moat is beginning to emerge: <strong>organisational judgment</strong>.</p><p><br>They discuss the difference between industry knowledge and company-specific context, why enterprise AI often struggles despite increasingly capable models, and why simply giving employees access to ChatGPT, Claude or Copilot does not necessarily make the organisation itself smarter.</p><p><br>The conversation explores:</p><ul><li>Why AI is making general industry knowledge less scarce</li><li>The difference between knowledge, context and judgment</li><li>Why enterprise AI needs to understand how a company actually operates</li><li>How institutional knowledge gets lost when experienced employees leave</li><li>The role of tacit knowledge in business decision-making</li><li>Why companies capture decisions but often fail to capture the reasoning behind them</li><li>How employees currently act as the manual context layer between AI and the enterprise</li><li>Why AI adoption should be measured by more than licences and usage</li><li>How organisational memory can become decision infrastructure</li><li>Why the next competitive advantage may be something your competitors cannot simply buy</li></ul><p>The first phase of enterprise AI was about giving people access to intelligence.</p><p>The next phase is about giving that intelligence context.</p><p>And the companies that learn how to capture and encode their history, reasoning, exceptions and judgment may build something far more defensible than access to any single model.</p><p><strong>Zeroe Perspectives</strong> explores the evolution of enterprise AI, and what changes when intelligence becomes abundant.</p>]]>
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      <pubDate>Thu, 20 Aug 2026 03:13:11 -0700</pubDate>
      <author>Zeroe</author>
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        <![CDATA[<p><strong>Zeroe Perspectives, Episode 1: The Knowledge Moat Is Ending</strong></p><p><br>For decades, deep industry knowledge was a competitive advantage.</p><p>It was valuable, scarce and difficult to replicate because it took years, sometimes decades, to accumulate.</p><p>AI is changing that.</p><p>Frontier models can now access and apply enormous amounts of specialised knowledge in seconds. What once required years of experience is becoming increasingly available to everyone.</p><p>So if your competitors can access the same intelligence you can, where does competitive advantage come from?</p><p><br>In the first episode of <strong>Zeroe Perspectives</strong>, Eric and Christina explore the idea that the traditional knowledge moat is disappearing, and that a new moat is beginning to emerge: <strong>organisational judgment</strong>.</p><p><br>They discuss the difference between industry knowledge and company-specific context, why enterprise AI often struggles despite increasingly capable models, and why simply giving employees access to ChatGPT, Claude or Copilot does not necessarily make the organisation itself smarter.</p><p><br>The conversation explores:</p><ul><li>Why AI is making general industry knowledge less scarce</li><li>The difference between knowledge, context and judgment</li><li>Why enterprise AI needs to understand how a company actually operates</li><li>How institutional knowledge gets lost when experienced employees leave</li><li>The role of tacit knowledge in business decision-making</li><li>Why companies capture decisions but often fail to capture the reasoning behind them</li><li>How employees currently act as the manual context layer between AI and the enterprise</li><li>Why AI adoption should be measured by more than licences and usage</li><li>How organisational memory can become decision infrastructure</li><li>Why the next competitive advantage may be something your competitors cannot simply buy</li></ul><p>The first phase of enterprise AI was about giving people access to intelligence.</p><p>The next phase is about giving that intelligence context.</p><p>And the companies that learn how to capture and encode their history, reasoning, exceptions and judgment may build something far more defensible than access to any single model.</p><p><strong>Zeroe Perspectives</strong> explores the evolution of enterprise AI, and what changes when intelligence becomes abundant.</p>]]>
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      <itunes:explicit>No</itunes:explicit>
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